<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study develops a financial performance evaluation system for S Group, employing a collaborative filtering algorithm to address the limitations inherent in traditional financial performance evaluation methodologies. Improvements have been made to the similarity measure method, data imputation technique, and rating prediction approach within the model. Subsequently, the financial status of S Group is scrutinized, with a thorough exploration of the input and output indicators, leading to the calculation of the efficiency values within the financial indicator system. Through sensitivity analysis, this research investigates the impact of input and output indicators on the outcomes derived from collaborative filtering. Based on the study, recommendations are formulated in alignment with the evaluation outcomes. The findings reveal that the average comprehensive efficiency of S Group over the past decade is 0.772, with a median comprehensive efficiency of 0.788, indicative of a robust financial condition. This research provides a valuable reference for the formulation of financial performance evaluation systems and the analysis of financial performance across various industries.</p>
</abstract>

This study develops a financial performance evaluation system for S Group, employing a collaborative filtering algorithm to address the limitations inherent in traditional financial performance evaluation methodologies. Improvements have been made to the similarity measure method, data imputation technique, and rating prediction approach within the model. Subsequently, the financial status of S Group is scrutinized, with a thorough exploration of the input and output indicators, leading to the calculation of the efficiency values within the financial indicator system. Through sensitivity analysis, this research investigates the impact of input and output indicators on the outcomes derived from collaborative filtering. Based on the study, recommendations are formulated in alignment with the evaluation outcomes. The findings reveal that the average comprehensive efficiency of S Group over the past decade is 0.772, with a median comprehensive efficiency of 0.788, indicative of a robust financial condition. This research provides a valuable reference for the formulation of financial performance evaluation systems and the analysis of financial performance across various industries.

Collaborative Filtering Algorithms in Financial Performance Evaluation Indicators for Intelligent Innovation Dynamic Research

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This study develops a financial performance evaluation system for S Group, employing a collaborative filtering algorithm to address the limitations inherent in...

Collaborative Filtering Algorithms in Financial Performance Evaluation Indicators for Intelligent Innovation Dynamic Research

Published Online: Jul 05, 2024

Page range: -

Received: Feb 25, 2024

Accepted: May 24, 2024

DOI: https://doi.org/10.2478/amns-2024-1709

Keywords
Collaborative filtering algorithm, Similarity measure, Sensitivity analysis, Financial performance

© 2024 Hong Liu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Collaborative Filtering Algorithms in Financial Performance Evaluation Indicators for Intelligent Innovation Dynamic Research

Published Online: Jul 05, 2024

Page range: -

Received: Feb 25, 2024

Accepted: May 24, 2024

DOI: https://doi.org/10.2478/amns-2024-1709

KeywordsCollaborative filtering algorithm, Similarity measure, Sensitivity analysis, Financial performance

© 2024 Hong Liu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Collaborative filtering algorithm, Similarity measure, Sensitivity analysis, Financial performance